Affiliation: Department of Diagnostic Radiology, Yale University School of Medicine, The Anlyan Center, New Haven, Connecticut, USA. lihong.jiang@yale.edu

ABSTRACT

Objective: The objective of this study was to characterize the changes in brain metabolism caused by antecedent recurrent hypoglycemia under euglycemic and hypoglycemic conditions in a rat model and to test the hypothesis that recurrent hypoglycemia changes the brain's capacity to utilize different energy substrates.

Research design and methods: Rats exposed to recurrent insulin-induced hypoglycemia for 3 days (3dRH rats) and untreated controls were subject to the following protocols: [2-(13)C]acetate infusion under euglycemic conditions (n = 8), [1-(13)C]glucose and unlabeled acetate coinfusion under euglycemic conditions (n = 8), and [2-(13)C]acetate infusion during a hyperinsulinemic-hypoglycemic clamp (n = 8). In vivo nuclear magnetic resonance spectroscopy was used to monitor the rise of(13)C-labeling in brain metabolites for the calculation of brain metabolic fluxes using a neuron-astrocyte model.

Conclusions: Our findings suggest that after antecedent hypoglycemia, glucose utilization is increased at euglycemia and decreased after acute hypoglycemia, which was not the case in controls. These findings may help to identify better methods of preserving brain function and reducing injury during acute hypoglycemia.

Figure 3: NMR spectra. A: Representative stack of in vivo 1H-[13C] difference spectra acquired over time, revealing gradual accumulation of brain [2-13C]acetate and its subsequent appearance in the stable metabolite pools of Glu4, Glu3, Gln4, and Gln3. B: Representative high-resolution 1H-[13C] spectra of brain tissue extracts used to further resolve the metabolite concentrations and enrichments of different carbon positions of glutamate-C4,3,2 (Glu4,3,2); glutamine-C4,3,2 (Gln4,3,2); GABA-C2,3,4, aspartate-C3 (Asp3); alanine-C3 (Ala3); and lactate-C3 (Lac3). Combination of these two measurements revealed the time courses of label accumulation in these metabolite pools, which were then used in the two-compartment model of brain metabolism to determine the metabolic fluxes. Cr, creatine; NAA, N-acetylaspartate; PCr, phosphocreatine.

Mentions:
Metabolic fluxes were determined by fitting the two-compartment model of astrocytic and neuronal metabolism depicted in Fig. 1, which is based on the time courses of13C-enrichment of the C4 position of glutamate and glutamine (Glu4 and Gln4) during the infusion of [2-13C]acetate (Fig. 3A) and the 13C-enrichment of Glu3 and Gln3 at the end of infusion (Fig. 3B). For a driver function, the measured time course of [2-13C]acetate in the brain was used instead of plasma acetate levels to eliminate uncertainties associated with acetate transport kinetics. Mass and isotopic flows from [2-13C]acetate to glial and neuronal glutamate and glutamine pools were expressed as coupled differential equations (see the supplementary materials, available in an online appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db08-1664/DC1) within the CWave 3.0 software package (25) running in Matlab 7.0 (Mathworks, Natick, MA). The equations were solved using a first-order Runge-Kutta algorithm, and fitting optimization was achieved using simulated annealing hybridized with a Levenberg-Marquardt algorithm (26) with fixed values for Vcyc/VtcaN and VkbN, where Vcyc indicates the rate of the glutamate/glutamine neurotransmitter cycle, VtcaN indicates the rate of neuronal tricarboxylic acid cycle, and VkbN indicates the rate of neuronal β-hydroxybutyrate utilization. The Vcyc/VtcaN ratio was calculated from the steady-state13C percentage enrichments of Glu4 and Gln4 from [2-13C]acetate according to the following (24): where “N” and “A” designate the neuronal and astroglial compartments, respectively. We assumed that glutamate was distributed between neurons (90%) and astroglia (10%) and glutamine was located entirely in astroglia. The steady-state enrichment of astroglial Glu4 was assumed to equal that of Gln4; thus, the percentage enrichment of neuronal glutamate is given by Glu4N = (Glu4 – Gln4 × 0.1)/0.9. The correction factor ci removes contributions to Glu4N (at the level of acetyl-CoA) from metabolism of13C-labeled plasma products derived from [2-13C]acetate metabolism in peripheral tissues, e.g., plasma glucose-C1 (and/or lactate-C3) and β-hydroxybutyrate (BHB)-C4/C2 (for details on calculation of this correction factor, see the supplemental materials).

Figure 3: NMR spectra. A: Representative stack of in vivo 1H-[13C] difference spectra acquired over time, revealing gradual accumulation of brain [2-13C]acetate and its subsequent appearance in the stable metabolite pools of Glu4, Glu3, Gln4, and Gln3. B: Representative high-resolution 1H-[13C] spectra of brain tissue extracts used to further resolve the metabolite concentrations and enrichments of different carbon positions of glutamate-C4,3,2 (Glu4,3,2); glutamine-C4,3,2 (Gln4,3,2); GABA-C2,3,4, aspartate-C3 (Asp3); alanine-C3 (Ala3); and lactate-C3 (Lac3). Combination of these two measurements revealed the time courses of label accumulation in these metabolite pools, which were then used in the two-compartment model of brain metabolism to determine the metabolic fluxes. Cr, creatine; NAA, N-acetylaspartate; PCr, phosphocreatine.

Mentions:
Metabolic fluxes were determined by fitting the two-compartment model of astrocytic and neuronal metabolism depicted in Fig. 1, which is based on the time courses of13C-enrichment of the C4 position of glutamate and glutamine (Glu4 and Gln4) during the infusion of [2-13C]acetate (Fig. 3A) and the 13C-enrichment of Glu3 and Gln3 at the end of infusion (Fig. 3B). For a driver function, the measured time course of [2-13C]acetate in the brain was used instead of plasma acetate levels to eliminate uncertainties associated with acetate transport kinetics. Mass and isotopic flows from [2-13C]acetate to glial and neuronal glutamate and glutamine pools were expressed as coupled differential equations (see the supplementary materials, available in an online appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db08-1664/DC1) within the CWave 3.0 software package (25) running in Matlab 7.0 (Mathworks, Natick, MA). The equations were solved using a first-order Runge-Kutta algorithm, and fitting optimization was achieved using simulated annealing hybridized with a Levenberg-Marquardt algorithm (26) with fixed values for Vcyc/VtcaN and VkbN, where Vcyc indicates the rate of the glutamate/glutamine neurotransmitter cycle, VtcaN indicates the rate of neuronal tricarboxylic acid cycle, and VkbN indicates the rate of neuronal β-hydroxybutyrate utilization. The Vcyc/VtcaN ratio was calculated from the steady-state13C percentage enrichments of Glu4 and Gln4 from [2-13C]acetate according to the following (24): where “N” and “A” designate the neuronal and astroglial compartments, respectively. We assumed that glutamate was distributed between neurons (90%) and astroglia (10%) and glutamine was located entirely in astroglia. The steady-state enrichment of astroglial Glu4 was assumed to equal that of Gln4; thus, the percentage enrichment of neuronal glutamate is given by Glu4N = (Glu4 – Gln4 × 0.1)/0.9. The correction factor ci removes contributions to Glu4N (at the level of acetyl-CoA) from metabolism of13C-labeled plasma products derived from [2-13C]acetate metabolism in peripheral tissues, e.g., plasma glucose-C1 (and/or lactate-C3) and β-hydroxybutyrate (BHB)-C4/C2 (for details on calculation of this correction factor, see the supplemental materials).

Affiliation:
Department of Diagnostic Radiology, Yale University School of Medicine, The Anlyan Center, New Haven, Connecticut, USA. lihong.jiang@yale.edu

ABSTRACT

Objective: The objective of this study was to characterize the changes in brain metabolism caused by antecedent recurrent hypoglycemia under euglycemic and hypoglycemic conditions in a rat model and to test the hypothesis that recurrent hypoglycemia changes the brain's capacity to utilize different energy substrates.

Research design and methods: Rats exposed to recurrent insulin-induced hypoglycemia for 3 days (3dRH rats) and untreated controls were subject to the following protocols: [2-(13)C]acetate infusion under euglycemic conditions (n = 8), [1-(13)C]glucose and unlabeled acetate coinfusion under euglycemic conditions (n = 8), and [2-(13)C]acetate infusion during a hyperinsulinemic-hypoglycemic clamp (n = 8). In vivo nuclear magnetic resonance spectroscopy was used to monitor the rise of(13)C-labeling in brain metabolites for the calculation of brain metabolic fluxes using a neuron-astrocyte model.

Conclusions: Our findings suggest that after antecedent hypoglycemia, glucose utilization is increased at euglycemia and decreased after acute hypoglycemia, which was not the case in controls. These findings may help to identify better methods of preserving brain function and reducing injury during acute hypoglycemia.